Neural Monkey is a universal toolkit for training neural models for sequence-to-sequence tasks. The system has been successfully tested on machine translation, multimodal machine translation, or automatic post-editing. It can be used, however, for many other tasks, including image captioning, part-of-speech tagging, sequence classification, etc.

Neural Monkey's primary goal is to allow for fast prototyping and easy extension, which makes it a toolkit-of-choice for researchers who want to implement and/or modify recently published techniques.

Neural Monkey is written in Python 3 and built on the TensorFlow library. It supports training on GPUs with a minimum required effort.

If you want to start using Neural Monkey, clone it from its GitHub page. There is a bunch of tutorials and plenty of other useful information either in the package README, or in the documentation.